Book Image

Julia Programming Projects

By : Adrian Salceanu
Book Image

Julia Programming Projects

By: Adrian Salceanu

Overview of this book

Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
About Packt


In this chapter, we have learned about working with dates and times in Julia. The language provides a powerful, yet accessible API that follows Julia's overall philosophy—you can start simple and augment your code as you become more knowledgeable. Thus, by default, the date/time objects use local time, ignoring complex details like time zones. However, time zone support is only one package away. We have seen how to extend Julia's Dates API by using the functionality provided by TimeZones.

Using our understanding of temporal data, we were able to take yet another step towards becoming proficient Julia programmers and learned about time series and the powerful TimeArray. We've seen how to plot time series with Plots, an extremely versatile plotting library for Julia—in fact, it's middleware providing a common API for a series of visualization packages, allowing us to swap backends as needed.

In the next chapter, we will continue our discussion of time series by performing analytics and...